Building on Complex Adaptive Systems theory and basic Agent Based Modeling knowledge presented in SPM4530, the Advanced course will focus on the model development process. The students are expected to conceptualize, develop and verify a model during the course, individually or in a group. The modeling tasks will be, as much as possible, based on real life research problems, formulated by various research groups from within and outside the faculty.
Study Goals The main goal of the course is to learn how to form a modeling question, perform a system decomposition, conceptualize and formalize the system elements, implement and verify the simulation and validate an Agent Based Model of a socio-technical system.

This course presents real-world examples in which quantitative methods provide a significant competitive edge that has led to a first order impact on some of today's most important companies. We outline the competitive landscape and present the key quantitative methods that created the edge (data-mining, dynamic optimization, simulation), and discuss their impact.

Lean thinking, as well as associated processes and tools, have involved into a ubiquitous perspective for improving systems particularly in the manufacturing arena. With application experience has come an understanding of the boundaries of lean capabilities and the benefits of getting beyond these boundaries to further improve performance. Discrete event simulation is recognized as one beyond-the-boundaries of lean technique. Thus, the fundamental goal of this text is to show how discrete event simulation can be used in addition to lean thinking to achieve greater benefits in system improvement than with lean alone. Realizing this goal requires learning the problems that simulation solves as well as the methods required to solve them. The problems that simulation solves are captured in a collection of case studies. These studies serve as metaphors for industrial problems that are commonly addressed using lean and simulation.

" This intensive micro-subject provides the necessary skills in Microsoftĺ¨ Excel spreadsheet modeling for ESD.71 Engineering Systems Analysis for Design. Its purpose is to bring entering students up to speed on some of the advanced techniques that we routinely use in analysis. It is motivated by our experience that many students only have an introductory knowledge of Excel, and thus waste a lot of time thrashing about unproductively. Many people think they know Excel, but overlook many efficient tools, such as Data Table and Goal Seek. It is also useful for a variety of other subjects."

GEO is a simulation game for business management that can be used either as a supplemental exercise to a lecture- or case-intensive course, a core component of an experiential-intensive course, or as a competitive event for assessment. The game is especially suited for courses in management principles, international business, entrepreneurship, and strategic management.

Presents and solves chemical engineering problems in an industrial context, with applications varying by semester. Emphasis on the integration of fundamental concepts with approaches of process design. Emphasis on problems that demand synthesis, economic analysis, and process design .This course introduces students to methods and background needed for the conceptual design of continuously operating chemical plants. Particular attention is paid to the use of process modeling tools such as Aspen that are used in industry and to problems of current interest. Each student team is assigned to evaluate and design a different technology and prepare a final design report. For spring 2006, the theme of the course is to design technologies for lowering the emissions of climatically active gases from processes that use coal as the primary fuel.

The lectures introduce a number of topics that are important for IWRM and the modeling exercise. The lectures introduce water management issues in the Netherlands, Rhine Basin, and Volta Basin. The role-play is meant to experience some of the social processes that, together with technical knowledge, determine water management.

This course covers the fundamental principles, practices and tools of Lean Six Sigma methods that underlay modern organizational productivity approaches applied in aerospace, automotive, health care, and other sectors. It includes lectures, active learning exercises, a plant tour, talks by industry practitioners, and videos. One third of the course is devoted to a physical simulation of an aircraft manufacturing enterprise or a clinic to illustrate the power of Lean Six Sigma methods.

The course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

We hope readers will take away three ideas from this book in addition to forming a foundation of statistical thinking and methods.

(1) Statistics is an applied field with a wide range of practical applications.

(2) You don't have to be a math guru to learn from interesting, real data.

(3) Data are messy, and statistical tools are imperfect. However, when you understand the strengths and weaknesses of these tools, you can use them to learn interesting things about the world.

Quantitative techniques of operations research with emphasis on applications in transportation systems analysis (urban, air, ocean, highway, and pickup and delivery systems) and in the planning and design of logistically oriented urban service systems (e.g., fire and police departments, emergency medical services, and emergency repair services). Unified study of functions of random variables, geometrical probability, multi-server queuing theory, spatial location theory, network analysis and graph theory, and relevant methods of simulation. Computer exercises and discussions of implementation difficulties.

Maneuvering motions of surface and underwater vehicles. Derivation of equations of motion, hydrodynamic coefficients. Memory effects. Linear and nonlinear forms of the equations of motion. Control surfaces modeling and design. Engine, propulsor, and transmission systems modeling and simulation during maneuvering. Stability of motion. Principles of multivariable automatic control. Optimal control, Kalman filtering, loop transfer recovery. Term project: applications chosen from autopilots for surface vehicles; towing in open seas; remotely operated vehicles.

This course covers the mathematical techniques necessary for understanding of materials science and engineering topics such as energetics, materials structure and symmetry, materials response to applied fields, mechanics and physics of solids and soft materials. The class uses examples from the materials science and engineering core courses (3.012 and 3.014) to introduce mathematical concepts and materials-related problem solving skills. Topics include linear algebra and orthonormal basis, eigenvalues and eigenvectors, quadratic forms, tensor operations, symmetry operations, calculus of several variables, introduction to complex analysis, ordinary and partial differential equations, theory of distributions, and fourier analysis. Users may find additional or updated materials at Professor Carter's 3.016 course Web site.

Modelling is about understanding the nature: our world, ourselves and our work. Everything that we observe has a cause (typically several) and has the effect thereof. The heart of modelling lies in identifying, understanding and quantifying these cause-and-effect relationships.

A model can be treated as a (selective) representation of a system. We create the model by defining a mapping from the system space to the model space, thus we can map system state and behaviour to model state and behaviour. By defining the inverse mapping, we may map results from the study of the model back to the system. In this course, using an overarching modelling paradigm, students will become familiar with several instances of modelling, e.g., mechanics, thermal dynamics, fluid mechanics, etc.

Strategic management is usually among the last courses of the business education curriculum. Taught from a top-management perspective, the course generally involves concepts, cases, and a business game. The balance among the work expected of students in studying concepts and engaging in cases and game vary greatly among institutions and their instructors.This narrative content is written for the strategic management course that is lighter-on-content and heavier-on-engagement. The content herein covers principles that are useful in practice. The student is told only what the student must be told, on the presumption that the student is intelligent enough to fill in the gaps, a presumption that should be reasonable for anyone aspiring to a top management position.To simplify the narrative, the discussion herein refers only to profit-making entities, labeled firms, even though much of the material is applicable also to not-for-profit organizations. Additionally, the revenue-generating output of firms are referred to always as products, even when the product could be a service, such as transportation.

Simulation games give practice in strategy implementation. Practice requires action that games demand. In a game, as in life, no action is an action and no strategy is a strategy.

Principles of thermal radiation and their application to engineering heat and photon transfer problems. Quantum and classical models of radiative properties of materials, electromagnetic wave theory for thermal radiation, radiative transfer in absorbing, emitting, and scattering media, and coherent laser radiation. Applications cover laser-material interactions, imaging, infrared instrumentation, global warming, semiconductor manufacturing, combustion, furnaces, and high temperature processing.

Students explore the definition and interpretations of the probability of an event by investigating the long run proportion of times a sum of 8 is obtained when two balanced dice are rolled repeatedly. Making use of hand calculations, computer simulations, and descriptive techniques, students encounter the laws of large numbers in a familiar setting. By working through the exercises, students will gain a deeper understanding of the qualitative and quantitative relationships between theoretical probability and long run relative frequency. Particularly, students investigate the proximity of the relative frequency of an event to its probability and conclude, from data, that the dispersion of the relative frequency diminishes on the order .

This activity leads students to appreciate the usefulness of simulations for approximating probabilities. It also provides them with experience calculating probabilities based on geometric arguments and using the bivariate normal distribution. We have used it in courses in probability and mathematical statistics, as well as in an introductory statistics course at the post-calculus level.

Survey of optimization methods for management of water resources. Linear, integer, nonlinear, and dynamic programming illustrated with case studies. Applications include reservoir and irrigation development, conjunctive use of surface and groundwater, capacity expansion, and sustainable resource development. This subject is concerned with quantitative methods for analyzing large-scale water resource problems. Topics covered include the design and management of facilities for river basin development, flood control, water supply, groundwater remediation, and other activities related to water resources. Simulation models and optimization methods are often used to support analyses of water resource problems. In this subject we will be constructing simulation models with the MATLABĺ¨ programming language and solving numerical optimization problems with the GAMS optimization package.